Generative Artificial Intelligence Leader

Tips: Provide a summary of the role, what success in the position looks like, and how this role fits into the organization overall.
Responsibilities
• Serve as the hands-on SME for predictive modelling, statistical modelling, Machine Learning, Deep Learning, Generative AI, and Agentic AI solutions.
• Architect and review solution design for complex analytics problems across patient journey analytics, HCP/payer/patient analytics, forecasting, and market mix modelling, recommendation engines.
• Provide technical oversight on model design, validation, performance benchmarking, and responsible/explainable AI practices.
• Drive adoption of Generative AI and Agentic AI frameworks (e.g., LLM-based copilots, RAG pipelines, multi-agent orchestration) for pharma commercial use cases.
• Guide teams on MLOps/LLMOps practices – model deployment, monitoring, retraining, and governance at scale.
Qualifications
• 15+ years of overall experience in Data Science / Advanced Analytics, including at least 5+ years of Pharma commercial analytics experience.
• Demonstrated hands-on capability (not only oversight) in predictive modelling, Machine Learning, Deep Learning, Generative AI, and Agentic AI solutions.
• Strong track record of client relationship management with top pharmaceutical/life sciences companies.
• Experience contributing to pre-sales, proposal development, and account growth in a consulting/analytics services environment.
• Excellent executive communication, storytelling, and stakeholder management skills.
• Strong business acumen with the ability to translate analytics into commercial impact and ROI.
Qualifications
• Master's or Ph.D. in Statistics, Computer Science, Data Science, Economics, Mathematics, Operations Research, Engineering, or a related quantitative discipline.

Work arrangement
No